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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jingrui Xie Bidong Liu Xiaoqian Lyu Tao Hong Basterfield, D. |
| Copyright Year | 2015 |
| Description | Author affiliation: Volume Position Manage., RWE npower, Solihull, UK (Basterfield, D.) || Energy Production & Infrastruct. Center, Univ. of North Carolina at Charlotte, Charlotte, NC, USA (Jingrui Xie; Bidong Liu; Xiaoqian Lyu; Tao Hong) |
| Abstract | The NPower Forecasting Challenge 2015 invited students and professionals worldwide to predict daily energy usage of a group of customers. The BigDEAL team from the Big Data Energy Analytics Laboratory landed a top 3 place in the final leaderboard. This paper presents a refined methodology based on the implementation during the competition. We first build the individual forecasts using several forecast techniques, such as Multiple Linear Regression (MLR), Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Random Forests (RF). We then select a subset of the individual forecasts based on their performance on a validation period, a.k.a. post-sample. Finally we obtain the final forecast by averaging the selected individual forecasts. The forecast combination on average yields a better result than the forecast from a single technique. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 254282 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781467373890 |
| DOI | 10.1109/NAPS.2015.7335138 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-04 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Forecasting Load forecasting Predictive models Market research Artificial neural networks Energy consumption Weather forecasting NPower Forecasting Challenge 2015 electric load forecasting forecasting combination forecast competition |
| Content Type | Text |
| Resource Type | Article |
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